Stress-induced hyperglycemia is a common occurrence in critically ill patients [1], regardless of health status (diabetic, pre-diabetic, or metabolically normal) prior to hospital admission. Elevated blood glucose (BG) and glycemic variability have been found to contribute to infection, slow wound healing, and short-term mortality [2], [3], [4], [5], [6], [7], [8]. In groundbreaking studies from 2001-2006, G. van den Berghe and colleagues reported improved outcomes for critically ill patients, particularly cardiac surgical patients, under Tight Glycemic Control (TGC) with a plasma glucose target range of 80-110 [9], [10], [11], inspiring many hospital Intensive Care Units (ICUs) to prescribe intensive insulin therapy with aggressive glucose targets for their patients. However, subsequent attempts to replicate improved outcomes via tight glycemic control have achieved mixed results. For example, van den Berghe et al. demonstrated no improvement in mortality rates and an increase in hypoglycemic events when TGC was applied to patients in a medical ICU [12]. Results from more recent studies are even less encouraging. In particular, the 2009 multicenter study, NICE-SUGAR, found that the attempt to achieve a 81-108 mg/dl target range increases both 90 day mortality and hypoglycemic events, the latter by 13-fold [13]. Subsequently the AACE/ADA, the Endocrine Society, and the ACP have relaxed their guidelines for inpatient glycemic control, advocating a presumably safer target range of 140-180 mg/dl [14]. However, the current recommended targets are controversial [15], [16]. None of the prior studies clarify whether tight glycemic targets (e.g. BG 80-110 mg/dl) are in themselves harmful or if the danger lies in the inadequacy of the available methods for achieving and maintaining safe glycemic outcomes.
From a process control perspective, many factors may contribute to the variability of reported glycemic outcomes [14], [17], [18]. Ineffective care coordination can lead to improper implementation of an intensive insulin therapy protocol [17], [18]. Even if a protocol is implemented as intended, point-of-care device variability can affect outcomes, with errors from less than 3% to as high as 20% [14], [19], [20]. Additionally, the choice of protocol may affect the glycemic outcome for each patient. Commonly used paper-based protocols vary in target range, method of insulin delivery (intravenous and/or subcutaneous), time between measurements, practitioner adherence, nutrition support, and insulin amount prescribed for a specific blood glucose measurement or change in blood glucose over time. Thus, different protocols will have different outcomes, regardless of the institution or patient population [14], [20], [21]. For these reasons, it is not clear that simply shifting the BG target range to higher targets (e.g. 140-180 mg/dl) will result in safer outcomes for patients.
There is a clear need for modeling tools that facilitate the design of insulin therapy protocols that support the needs of specific patient populations. In vivo evaluation of alternative insulin therapy protocols (whether paper-based or computer-assisted) is expensive, time consuming, and potentially dangerous [21], [22], [23], [24], [25], and further large studies are unlikely in light of NICE-SUGAR. Moreover, it is generally infeasible to directly compare different insulin protocols in the same set of patients.